The InclusionExclusion Principle
From the First Principle of Counting we have arrived at the commutativity of addition, which was expressed in convenient mathematical notations as
 Every group of objects A can be associated with a quantity  denoted A  called the number of elements in A.
 If X = A∪B and A∩B = Ø, then X = A + B.
The latter is a statement of legitimacy of counting by grouping. If a group of objects X is split into two groups  denoted A and B, which means that they have no common elements (
Since X = A∪B, the idea of counting by grouping can also be expressed as
(1)  If A∩B = Ø, then A∪B = A + B. 
This is exactly same statement with a somewhat different emphasis. Instead of splitting the whole into two groups, we start with two (disjoint, i.e. with no common elements) wholes and combine them into one. The latter form is suggestive of the question, What if A and B are not disjoint? Or is it?
Is it not too artificial to count sets that are not disjoint? After all, this would never happen with counting by grouping. Well, what can one say? Is it not what is called Turning an idea around in one's mind? Once the humankind began composing the story of counting, the plot acquired life and logic of its own. and this is how  by following its plot  we arrived at where we are today: masters of a vast amount of accumulated knowledge in control of fantastically powerful technology that could not have been foreseen at the beginning of the story. (Consider also such a question: two brothers have three siblings each. How many children are in the family?)
If A and B are not disjoint, we get the simplest form of the InclusionExclusion Principle:
(2)  A∪B = A + B  A∩B. 
Indeed, in A + B some elements have been counted twice (the common siblings of the two brothers). Which are they? The elements that were counted twice are exactly those that belong to A (one count) and also belong to B (the second count). In short, counted twice were the elements of A∩B. To obtain an accurate number A∪B of elements in the union we have to subtract from
Here's an argument that may appear more rigorous.
Since A∩B and
(3) 
A∪B = A + B  A A∩B + B  A = B, 
which, when added, yield (2).
The story of course does not end here. What about if there are three sets: A, B, C? For three sets, the InclusionExclusion Principle reads
(2')  A∪B∪C = A + B + C  A∩B  B∩C  A∩C + A∩B∩C 
We could derive (2') from (2) in the manner of (3)  and this is a good exercise in using settheoretical notations. But there is another approach with a more manageable generalization to the case of any finite number of sets, not just three. (You did not think we'd stop at (2')?)
Let x be an element of A∪B∪C. As such, it's counted once in the lefthand side of (2'). x may belong to 1, 2, or 3 sets A, B, C. Assume it belongs only to A. Then on the right of (2') it is counted only once in A.
Let x belong to A and B. On the right, it is counted in A, B, and A∩B  twice added, once subtracted.
Lastly, let x belong to all three sets A, B, C. It is then counted in every term of (2')  4 times added and 3 times subtracted  again adding up to 1.
In the more general case where there are n different sets A_{i}, the formula for the InclusionExclusion Principle becomes:
(4) 
What does (4) say? On the left is number of elements in the union of n sets. On the right, we first count elements in each of the sets separately and add the up. as we already know, if the sets A_{i} are not disjoint, some elements will have be counted more than once. Those are the elements that belong to at least two of the sets A_{i}, or the intersections A_{i}∩A_{j}. We wish to consider every such intersection, but each only once. Since
When we subtract the sum of the number of elements in such pairwise intersections, some elements may have been subtracted more than once. Those are the elements that belong to at least three of the sets A_{i}. We add the sum of the elements of intersections of the sets taken three at a time. (The condition
The process goes on with sums being alternately added or subtracted until we come to the last term  the intersection of all sets A_{i}. Whether it's added or subtracted depends on n: for
How does one prove (4)? Assume that an element x of
belongs to exactly r of the sets A_{i}. If that's the case, all intersections of more than r sets are empty  contain no elements. Moreover, all intersections in which one of sets does not contain x are also empty. Of the given r sets that do contain x, we may form
1 = C(r, 1)  C(r, 2) + C(r, 3)  .... + (1)^{r1}C(r, r) 
or,
1  C(r, 1) + C(r, 2)  C(r, 3) + .... + (1)^{r}C(r, r) = (1  1)^{r} = 0 
by the binomial theorem. This completes the proof of (4).
Sets A_{i} are often taken to be subsets of a larger set X such that each A_{i} is a collection of elements of X that share some property P_{i}.
is then the subset of X that consists of all elements of X having at least one of the properties P_{i}. Its complement
is the set of elements that have none of those properties:
from which

This leads to an additional form of (4)
(4') 
The lefthand side in (4') gives the number of elements of X that have none of the properties P_{i}.
Let X be the set of all permutations of m elements.
On the left, we got the number of derangements  permutations that move every single element  whose set is often denoted as D_{m}:
(5)  D_{m}  = m!  m·(m  1)! + C(m, 2)(m  2)!  ... + (1)^{m}C(m, m) 
= m! (1  1/1! + 1/2!  1/3! + ... + (1)^{m} / m!). 
We have encountered derangements while labeling boxes.
References
 V. K. Balakrishnan, Theory and Problems of Combinatorics, Schaum's Outline Series, McGrawHill, 1995
 J. Havil, Nonplussed!, Princeton University Press, 2007
 S. Lipschutz and M. L. Lipson, 2000 Solved Problems in Discrete Mathematics, McGrawHill, 1992
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